Effect of Genetic Polymorphisms on the Pharmacokinetics of Deferasirox in Healthy Chinese Subjects and an Artificial Neural Networks Model for Pharmacokinetic Prediction

• Published in: European journal of drug metabolism and pharmacokinetics Vol. 45; no. 6; pp. 761 - 770
• Main Authors: Chen, Jinliang, Xu, Yichao, Lou, Honggang, Jiang, Bo, Shao, Rong, Yang, Dandan, Hu, Yin, Ruan, Zourong
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2020
• Subjects: Biomedical and Life Sciences; Biomedicine; Human Physiology; Medical Biochemistry; Original Research Article; Pharmaceutical Sciences/Technology; Pharmacology/Toxicology; Pharmacy
• ISSN: 0378-7966; 2107-0180; 2107-0180
• DOI: 10.1007/s13318-020-00647-z

Background and Objective Deferasirox is an oral iron chelator used to reduce iron levels in iron-overloaded patients with transfusion-dependent anemia or non-transfusion-dependent thalassemia. This study investigated the effects of genetic polymorphisms on the pharmacokinetics of deferasirox in healthy Chinese subjects and constructed a pharmacokinetic prediction model based on physiologic factors and genetic polymorphism data. Methods Twenty-eight subjects were enrolled in a randomized, open-label, two-period crossover study, and they received a single dose of one of two formulations of deferasirox (20 mg/kg) with a 7-day washout interval between the two periods. The plasma defersirox concentration was determined using a validated liquid chromatography-tandem mass spectrometry method, and pharmacokinetic parameters were calculated using the noncompartmental method. The polymorphisms of uridine diphosphate glucuronosyltransferase 1A1 ( UGT1A1 ), UGT1A3 , multidrug resistance protein 2 ( MRP2 ), cytochrome P450 1A1 ( CYP1A1 ), and breast cancer resistance protein 1 ( BCRP1) were genotyped using Sanger sequencing. A back-propagation artificial neural network (BP-ANN) model was used to predict the pharmacokinetics. Results The UGT1A1 rs887829 C  >  T single-nucleotide polymorphism (SNP) significantly influenced the area under the plasma concentration-time curve and the terminal half-life. Neither the MRP2 rs2273697 G  >  A SNP nor BCRP1 rs2231142 G  >  T SNP altered the absorption, disposition, and excretion of the drug. The BP-ANN model had a high goodness-of-fit index and good coherence between the predicted and measured concentrations ( R 2  = 0.921). Conclusion Metabolic enzyme-related genetic polymorphisms were more strongly associated with the pharmacokinetics of deferasirox than membrane transporter-related genetic polymorphisms in the Chinese population. Trial registration : www.Chinadrugtrials.org.cn CTR20191164